Your VMware Environment Is Already Running the Business. Could It Be Running Your AI?

USA, Oct 14, 2026

AI delivers measurable value for enterprises that focus on fundamentals, such as quality data, AI-native services, and efficient use of infrastructure.

The challenge is adopting those fundamentals while keeping complexity in check. Additional AI environments, for instance, bring new operational, security, governance, and skills requirements. One way to bypass these obstacles is by building on infrastructure teams already know and trust.

For enterprises running VMware, much of that foundation is already in place. The same environment running the business today can also be the foundation for running AI.

Starting with the Foundation You Already Have

Many AI initiatives begin with a dedicated AI stack, complete with new platforms, tools, and processes. This approach adds overhead that can come in the form of new security controls, governance policies, operational skills, hardware, and more.

For VMware customers, however, their existing environment can serve as that very same AI foundation. It already holds enterprise data, enforces established security policies, and runs on processes IT teams use day to day. 

With the right approach, teams can build a foundation for enterprise AI initiatives with the same environment that runs the business. 

Bring Enterprise Data to AI

AI delivers real value when it has secure access to an organization's core data. Yet as most IT leaders know, data protection is a top concern when it comes to AI. 

Recent research from Broadcom clearly highlighted this challenge: IT leaders named data protection and privacy (37%) and security and control (36%) as the biggest new demands AI is placing on enterprise IT.

37%
name data protection and privacy as a top new AI demand

36%
name security and control as a top new AI demand

-Broadcom, Private Cloud Outlook 2026

For VMware customers, key enterprise data - such as customer records, financial information, and intellectual property - already lives in VMware environments, which means it is already protected by established security controls.

By running AI applications and models on VMware Cloud Foundation (VCF), right alongside that data, organizations keep information within existing security boundaries and reduce the risk and cost of moving data between environments. The same access policies, audit trails, and compliance processes that protect business applications can then be extended to AI workloads.

Work with the AI Services Built into VCF

AI is now a native part of VMware's private cloud platform. 

VCF Private AI Services, included as part of VCF, give enterprises one unified platform for AI and traditional workloads. These services include:

  • GPU monitoring
  • A model store
  • Model runtime
  • Agent builder
  • Vector database
  • Data indexing and retrieval

This means that teams can serve models behind an API gateway and build RAG with an integrated vector database, all managed through the VCF Automation interface.

Broadcom continues to build on this foundation with solutions such as VMware Private AI Cloud. 

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Introduced at VMware Explore 2026, it provides a single platform for inference workloads, agentic applications, containerized services, and virtual machines under one operational model and security posture.

Maximize Every GPU Investment

GPUs are among the most expensive resources in the data center, and underused capacity raises the cost of every AI workload. 

VMware AI Factory, offered through VCF, pools and shares GPU resources across the organization, so teams can run multiple models on shared hardware and get more value from every GPU.

Multi-tenant model sharing lets different lines of business use the same AI models through isolated namespaces. Each team's data stays private, and the organization avoids redundant model deployments that consume valuable GPU capacity.

VCF also supports AI workloads on both NVIDIA and AMD GPUs. That flexibility preserves hardware choice and helps organizations improve infrastructure utilization as AI needs grow.

Future-Ready AI with VMware

Broadcom has also outlined several upcoming capabilities for VCF Private AI Services, including:

  • An AI Gateway that routes prompts to the most suitable on-premises or cloud models based on factors such as use case and token cost
  • A Secure Agent Framework that adds sandboxing for agent-generated code 
  • An agent harness that controls which tools agents can access and how their outputs are validated
  • Model Autoscaling that automatically scales models up or down based on latency and session thresholds

With support for more than 150 open-source models through vLLM, VCF's default model runtime, these developments help ensure teams can keep pace with AI's rapidly evolving landscape.

Running Business and AI with One Foundation

Enterprise AI depends on a foundation of trusted data, consistent governance, and secure, efficient infrastructure. 

For organizations running VMware, much of that foundation is already in place, and with Broadcom's continued AI investments, it will keep evolving for years to come.

Contact Logicalis to learn how you can run your business and your AI on one foundation.

 

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